Enhancing fabric TENG performance through optimized compression mechanics in smart IoT carpets, for energy harvesting and movement sensing
Akshaya Kumar Aliyana, Danying Yang, George K. Stylios
Abstract
Fabric Triboelectric Nanogenerators (F-TENGs) are crucial for wearable technology, offering sustainable energy generation and enhanced sensing capabilities on a single device platform, eliminating the need for conventional batteries and added sensors. However, developing fabric-based TENGs with outstanding triboelectric performance—featuring high power density, stability, comfort, washability, reliability, and sensing capabilities —is still challenging. The mechanics of fabric, particularly its compressive properties, play a crucial role in influencing the energy output of TENGs. Understanding this relationship is key to enhancing energy generation capabilities. In this study, we explored the impact of fabric compressive mechanics on a novel Core Spun Yarn (CSY) based dual-effect fabric TENGs energy and sensing. We designed five distinct knitted fabric structures; single bed, double bed, half cardigan, full cardigan, and ripple structures, and tried to explain their mechanical behavior in relation to TENG performance, focusing on parameters such as Work Done in Compression (WC), Compressive Resilience (RC), and Compressive Linearity (LC). We observed a strong positive correlation between the compressive energy (0.03 gf. cm/cm²), resilience (40 %), linearity (0.5), and density (28 cm²) of the full cardigan knitted structure and the electrical output of the TENGs in a contact-separation configuration. These findings reveal the influence of fabric mechanics to TENG output and explain why the full cardigan fabric is the most optimal choice for fabric-based TENGs, achieving a maximum peak power of 120 mW and a peak power density of 588 mW/m² at an external impedance of 1 GΩ, a frequency of 8 Hz, and a normal pressure of 50 N. Based on this fabric, we have developed a complete IoT-enabled intelligent carpet system for the precise detection of movement. This research provides a method for creating dual-effect fabric TENG devices, paving the way for the development of TENG fabrics that can simultaneously perform real-time sensing and energy generation. • This study examines how fabric compressive mechanics affect the electrical performance of Core-Spun Yarn-based dual-effect T-TENGs. • Five knitted fabric structures (single bed, double bed, half cardigan, full cardigan, ripple) were analyzed for optimal TENG output. • Key compressive parameters (WC, RC, LC) were evaluated to establish their correlation with TENG output efficiency. • The full cardigan fabric achieved a maximum peak power of 120 mW and a peak power density of 588 mW/m². • An IoT-enabled smart carpet system was developed, using optimized fabric for real-time movement detection, energy generation, and safety.